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The interdisciplinary curriculum has been developed by leading faculties from six top departments and schools of the University of Washington:
Our industry council supports curriculum innovation and ensures that the security level is innovative and industry-equivalent. The industry council includes estimated Data Science experts from Amazon, Boeing, Google, HCL technologies, Microsoft and Seattle children's hospital.
To earn the Master of Science in Data Science graduation, students must complete 45 credits consisting of eight core courses (40 credits) and a two-quarter-capstone project (5 credits).
The Master of Science in Data Science Curriculum ensures that the width and depth of knowledge is needed for a successful career in data science. It emphasizes practical skills in the application of relevant skills through courses in statistical modeling, data management, machine learning, data visualization, software engineering, research design, data ethics and user experience. Depending on the course, students can expect a focus on Python and R programming and some jobs in Java.
Many of the courses emphasize team-based data analysis and engineering work and will help to work in small groups to complete one or more guided Practicum projects per quarter. The last two quarters include a Capstone project in which students solve a real challenge for an external organization.
Course descriptions are available here.
The Master of Science in the Data Science program is available in two formats: full time or part time. Both formats offer the same industry-relevant curriculum, the same world-class faculty and the same Premier Data Science degree. You can choose the format that meets your academic and professional goals.
Our 1.5-year-old, full-time program offers a quick and clear way to earn your master's degree and accelerate your career in data science. Our full-time program is an excellent fit for recent college graduates who want to start their career in data science. It is also a strong option for experienced professionals who render career or drive their career by completely immersing themselves in a data science program. Our full-time students come from all over the country and around the world with the aim of accelerating their data science career. Students on an F-1 visa have to register in the full-time program.
Our part-time program allows students to build their skills without breaking their career while the same state-of-the-art curriculum offers full-time format. The comfortable evening classes enable students to earn a data science degree without taking their career. It is advantageous for Seattle-based professionals. Our current part-time students include professionals who are surrounded by organizations in the entire Seattle area, including Amazon, Boeing, Fred Hutchinson, Microsoft and T-Mobile, very close to Amazon, Boeing, Fred Hutchinson, Microsoft and T-Mobile . Our part-time program allows the students to accept tomorrow, what they learn today at their workplace.
The students generally lead through their course work as cohort. One of the benefits of cohort experience is that students can build their professional network.The students in the MSDS program come from a variety of professional and academic backgrounds that enable students to build connections throughout the industries. By building these professional connections, students can drive their career development.
When students build professional connections, they also create friendships with their cohort members. Because a cohort spends a large part of their time together, students can build friendships that take even after completing the program. The sense of community within an MSDS cohort also translates into a dynamic learning environment. Many of the courses are interactive and emphasized group discussions and team-based orders. This allows students to learn not only of their teachers, but also of their members of the cohort.
new application opens
10 January, pm (Pacific)
International application period
January 18, pm (Pacific)
domestic application period
approval decisions announced
28 September 2022
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